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Consistency-preserving Caching of Dynamic Database Content

机译:动态数据库内容的保持一致性的缓存

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With the growing use of dynamic web content generated from relational databases, traditional caching solutions for throughput and latency improvements are ineffective. We describe a middleware layer called Ganesh that reduces the volume of data transmitted without semantic interpretation of queries or results. It achieves this reduction through the use of cryptographic hashing to detect similarities with previous results. These benefits do not require any compromise of the strict consistency semantics provided by the back-end database. Further, Ganesh does not require modifications to applications, web servers, or database servers, and works with closed-source applications and databases. Using two benchmarks representative of dynamic web sites, measurements of our prototype show that it can increase end-to-end throughput by as much as twofold for non-data intensive applications and by as much as tenfold for data intensive ones.
机译:随着从关系数据库生成的动态Web内容的使用越来越多,传统的缓存解决方案无法提高吞吐量和延迟。我们描述了一个称为Ganesh的中间件层,该层可以减少传输的数据量,而无需对查询或结果进行语义解释。它通过使用加密散列来检测与先前结果的相似性来实现这种减少。这些好处不需要损害后端数据库提供的严格一致性语义。此外,Ganesh不需要修改应用程序,Web服务器或数据库服务器,并且可以与封闭源应用程序和数据库一起使用。使用代表动态网站的两个基准,对我们的原型的测量表明,对于非数据密集型应用程序,它可以将端到端吞吐量提高两倍,对于数据密集型应用程序,则可以提高十倍。

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